The biggest problem with artificial intelligence (AI) is that most people have heard of it, but they have no idea what it actually means. As a result, the “average” member of the public hardly ever uses AI tools in his or her everyday activities.
The term “artificial intelligence” was actually coined back in 1956, while the term “machine learning” was first mentioned in 1959 (see Picture 1 below).
For the time being, the term “artificial intelligence” implies making use of very good, useful, self-adjusting algorithms that work well when processing large sets of available data and information.
However, “artificial intelligence” is definitely not about intelligence. This is because intelligence implies the ability to invent new things and generate new information.
Right now only the human brain is capable of inventing new things and generating new information. And scientists still have only sketchy knowledge about the way our human brain functions: it is made up of at least 85 billion nerve cells or neurons, along with thousands of other types of cells. As the New York Times put it: “Researchers identified some 3,300 types of brain cells, an order of magnitude more than was previously known, and have only a dim notion of what most of them do” (see Reference 1 and Picture 2 below).
And you cannot reproduce any “artificial” brain unless you know exactly how the “natural” brain works.
The chances that our understanding of how the human brain works will increase significantly in the near future are very low.
Therefore, there are no chances that very good, useful, and self-adjusting algorithms will be transformed into something similar to human consciousness (aka “artificial general intelligence”) in the foreseeable future. Because we still do not know what is the essence of human consciousness.
I do not rely on ChatGPT because it is like relying on everything that is posted on the web, while AI-generated texts are easily recognized because they sound artificial and “plastic” like modern pop music.
I do not use personalized content recommendations and suggestions because they are repetitive, unimaginative, and predictable by relying on my searches in the past rather than on my current interests.
I do not rely on Wikipedia articles because they should be checked and re-checked by reading scholarly and academic sources. For the same reason I do not rely on Hollywood movies or Netflix series to get an idea about various historical events because this is the best way to be misinformed.
I do not use smart TVs, refrigerators, vacuum cleaners, or voice assistants because they would make my life just marginally more comfortable, while being useless overall.
I use machine translation. It is definitely useful because it is fast. But its quality is still so low and often misleading in contrast to professional human translation that it needs to be manually reviewed and corrected. It is like providing first aid by a stranger before seeing a real doctor.
As Euromonitor International put it, “Last year, Ask AI was all about ongoing experimentation and shifting expectations of generative AI solutions. Increased adoption also raised skepticism as consumers pointed to flaws in output, leading to the AI Ambivalent trend for 2025” (see Reference 2 below).
Many investors agree. As the Reuters news agency has recently reported, “European companies that are spending big on generative artificial intelligence need to start showing returns on their massive outlays by next year, or risk investors losing patience after they paid sky-high prices to join the market boom” (see Reference 3 below).
Such skepticism is perfectly acceptable when you deal with any new, untested technology because there is no guarantee that this new, untested technology will go mainstream or even become dominant in the future.
The thing is that the amount of investments in the area of artificial intelligence has already exceeded $1 trillion. Another $500 billion is expected to be invested in the United States alone (see Picture 3 below).
I would assume that is enough money to hire a person who would be able to compile a list of practical AI applications on a single A4 sheet to explain where artificial intelligence is being used now in addition to being useful, fast-working, self-adjusting algorithms when processing large sets of available information. And, most importantly, how AI tools can be used by ordinary people in their daily lives today.
The Business Insider reported that “OpenAI aired its first-ever Super Bowl ad on Sunday, making a $14 million statement that artificial intelligence belongs in the same category as fire, the wheel, and the internet” (see Reference 4 and Picture 4 below).
If I lose access to electricity, running water, Internet connections, the ability to travel by car, buy a medicine, have a CT or MRI scan, it will be a disaster.
If the existing version of “artificial intelligence” fails or disappears altogether what is going to happen?
Or is it just one of those potentially breakthrough technologies, like nuclear fusion, a cure for cancer, quantum computing, or interplanetary travel where further progress has been either painstakingly slow or has stalled altogether since the 1960s and 1970s?
The most reliable and satisfying life strategy is achieving results that exceed initial expectations. The initial expectations with respect to artificial intelligence are so high and uncertain at the same time that it is all becoming increasingly disturbing.
References:
1. “The Human Brain Has a Dizzying Array of Mystery Cells”, Carl Zimmer, The New York Times, October 12, 2023.
2. “What Are the Top Consumer Trends in 2025?”, Alison Angus, Euromonitor International, January 23, 2025.
3. “European Investors Say Clock Is Ticking for AI Adopters to Deliver”, Lucy Raitano, Reuters, March 26, 2025.
4. “OpenAI Compares ChatGPT to Humankind’s Greatest Inventions in Its First-Ever Super Bowl Ad”, Effie Webb, The Business Insider, February 10, 2025.
